Summary The mission of the Data Platform team is to provide our engineers and data scientists a cutting edge, reliable and easy to use infrastructure for ingesting, storing, processing, and interacting with data and ultimately help the teams that build data intensive applications be successful. We are looking for a DevOps/Backend Engineer responsible for the backend infrastructure that powers the AI / ML Data teams applications and workflows for analytics and machine learning.
We are looking for DevOps engineers with ElasticSearch or OpenSearch expertise who want to bring their passion for infrastructure to build world class infrastructure products.
Responsibilities:
Manage and operate our data infrastructure hosted in AWS
Monitor and maintain the health of OpenSource
Collaborate across AI/ML teams to analyze and optimize infrastructure for different forms of data needs
Evolve and modify data platform and tools to meet scalability needs
Diagnose, fix, improve, and automate complex issues across the platform to ensure maximum uptime and performance
Establish SLA’s for all indexing and search use cases in production
Write code, documentation, participate in code reviews, and mentor other engineers
Requirements:
5-10+ years of experience DevOps with OpenSearch, ElasticSearch, Solar or equivalent text search query engines
5+ years of experience configuring, scaling, and troubleshooting data processing and analytics infrastructure
Java, Python or other coding languages backend experience is required. Java is preferred.
Must be a strong problem-solver that knows how to debug and know how to respond issues in a timely manner
Desired Skillsets:
Passionate about Data Processing and Analytics Technologies and building large backend systems
AWS and EKS is a major plus
Great communicator and collaborator. Not afraid to ask for help
Experience with alerting, monitoring and remediation automation in a large scale distributed environment
Duration: 3 months with possibility for extension Location: 100% Remote or Seattle, WA (Hybrid schedule – 3 days onsite)
